Objective To explore the role of high endothelial venule (HEV) in chronic obstructive pulmonary disease (COPD) at the single cell level. Methods A total of 219257 cells from the lung tissues of 18 COPD patients and 28 healthy controls in the GEO public database (GSE136831) were used to analyze the relationship between HEV with T lymphocytes, B lymphocytes, and dendritic cells. Results Endothelial cells were extracted using single cell analysis technique, and sorting out venous endothelium, CCL14, IGFBP7, POSTN were used as marker genes for HEV endothelial cells. The ratio of HEV endothelial cells was also identified as up-regulated expression in COPD. The function of the differential genes of HEV endothelial cells was analyzed, suggesting the presence of immune regulation. By trajectory analysis, it was suggested that the differential genes of HEV endothelial cells were enriched for extracellular matrix deposition in late development. Finally, by receptor-ligand pairing, it was suggested that HEV endothelial cells was recruited through a series of ligands with T lymphocytes, B lymphocytes, and dendritic cells. Conclusions HEV endothelial cells are elevated in COPD and have an immunomodulatory role by secreting a series of ligands after recruiting T lymphocytes, B lymphocytes as well as dendritic cells for immune action. HEV may be a potential target for the study of COPD therapy.
ObjectiveTo explore the differentially expressed genes (DEGs) in venous leg ulcer (VLU) by bioinformatics, and further explore the molecular mechanism of the disease, predict early diagnostic markers and treatment targets.MethodsThe expression profiles of VLU were downloaded from the gene expression omnibus (GEO) database, the DEGs of VLU and inflammatory phase of normal skin healing were identified by R software and used to perform gene ontology (GO) and KEGG pathway enrichment analysis, obtaining the key genes of the pathway. We analyzed the proteins of protein interaction (PPI) network by STRING database and Cytoscape 3.2.1 software to obtain hub genes.ResultsA total of 409 DEGs were obtained, including 173 upregulted genes and 236 downregulted genes. The GO analysis showed that the upregulated DEGs mainly distributed in collagen-containing extracellular matrix (ECM), cornified envelope and collagen trimer, involved in biological processes such as skin development, keratinocyte differentiation and cornification, which mediated molecular functions such as ECM structural constituent, ECM structural constituent conferring tensile strength and integrin binding. The downregulated DEGs mainly distributed in tertiary granule, secretory granule membrane and tertiary granule membrane cornification, involved in biological processes such as response to chemokine, leukocyte migration and neutrophil chemotaxis, which mediated molecular functions such as chemokine activity, chemokine receptor binding and cytokine activity. KEGG pathway enrichment analysis results showed that the upregulated DEGs were mainly enriched in ECM-receptor interaction and protein digestion and absorption pathways, collagen type Ⅰ alpha1 chain (COL1A1), collagen type Ⅰ alpha2 chain (COL1A2), and collagen type Ⅵ alpha 6 chain (COL6A6) were the key genes of pathway; the downregulated DEGs were mainly enriched in Staphylococcus aureus infection, Toll-like receptor signaling pathway and leukocyte transendothelial migration pathways, interleukin (IL)-1β, C-X-C motif chemokine ligand 8 (CXCL8), IL-10, matrix metalloproteinase (MMP)1, and MMP9 were the key genes of pathway. The hub core genes of the PPI network were formyl peptide receptor (FPR)1, FPR2, IL-1β, IL-10, and CXCL8.ConclusionsThe results of this study indicate that the genes and signaling pathways involved in COL1A1, COL1A2, COL6A6, IL-1β, CXCL8, IL-10, MMP1, and MMP9 affect the healing of VLU. FPR1, FPR2, IL-1β, IL-10, and CXCL8 can be used as potential therapeutic targets.
The purpose of this paper is to present the research on the molecular biological characteristics of proto-oncogene pim-2 and to analyze the related mechanism. Proto-oncogene pim-2 was studied and analyzed by the bioinformatics method and technology. With an online server, the chromosomal localization of pim-2 gene was analyzed, and the exon, open reading frame, CpG island and miRNAs complementary fragments and the like were predicted. With bioinformatics software, the physicochemical property of transcription protein of proto-oncogene pim-2 and various modification sites of protein sequence, such as ubiquitination and glycosylation, were predicted, the antigenic index was calculated, and the spatial structural was modeled. The research findings showed that the proto-oncogene pim-2 comprised six exons, the CDS (coding sequence) transcribed a section of peptide chain including 311 amino acids, a gene promoter has a CpG island, and the 3'UTR region contains an miRNA gene. The molecular weight of the Pim-2 protein was 34, 188.47, the isoelectric point was 5.78, the instability index was 45.87, and the extinction coefficient was 279nm. A plurality of covalent modification sites, two ubiquitination sites, four glycosylation sites, an SUMO sumoylation site, a nitrosation site, two palmitoylation sites and sixteen regions with higher antigenic index were distributed in the protein sequence. This research showed that the related regions and modification sites distributed on the sequence of proto-oncogene pim-2 were closely related to the carcinogenic effect thereof.
ObjectiveTo observe the expressions of miR-143-3p in gastric cancer cells and gastric carcinoma tissues with its clinical significance, and to analyze the target genes with enriched pathway by using bioinformatics methods.MethodsThe expressions of miR-143-3p in different differentiation gastric cancer cells and normal gastric mucosa cell line, and the expressions in gastric cancer tissues and adjacent tissues were detected by real-time fluorescent quantitative PCR. In addition, OncomiR and YM500 databases were used to analyze the expression of miR-143-3p in gastric cancer tissues compared with adjacent tissues. Furthermore, the targets of miR-143-3p were predicted by using the software of miRecords website database, and at least three software-supported target genes were chosen to analyze the enriched the signal pathways in which the target gene was involved with DAVID 6.7 software.ResultsThe expressions of miR-143-3p in the different differentiation degree of gastric cancer cells compared with normal gastric mucosa cell line were downregulated (P<0.001), and the expression of miR-143-3p in gastric cancer tissues compared with adjacent tissues was also downregulated (downregulated in 36 cases, upregulated in 18 cases, and no alteration in 4 cases). The expression of miR-143-3p in gastric cancer tissues was associated with lymph node metastasis and invasion depth (P<0.05). Bioinformatics analysis results showed that the target genes of miR-143-3p were enriched in 38 signaling pathways associated with cancer.ConclusionMiR-143-3p is a down-regulated molecular marker in gastric cancer and a potentially clinically related tumor suppressor gene, which may be involved in the cancerous phenotype in carcinogenesis and development of gastric cancer.
Objective To explore the key genes, pathways and immune cell infiltration of bicuspid aortic valve (BAV) with ascending aortic dilation by bioinformatics analysis. Methods The data set GSE83675 was downloaded from the Gene Expression Omnibus database (up to May 12th, 2022). Differentially expressed genes (DEGs) were analyzed and gene set enrichment analysis (GSEA) was conducted using R language. STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) network and identify hub genes. The proportion of immune cells infiltration was calculated by CIBERSORT deconvolution algorithm. Results There were 199 DEGs identified, including 19 up-regulated DEGs and 180 down-regulated DEGs. GSEA showed that the main enrichment pathways were cytokine-cytokine receptor interaction, pathways in cancer, regulation of actin cytoskeleton, chemokine signaling pathway and mitogen-activated protein kinase signaling pathway. Ten hub genes (EGFR, RIMS3, DLGAP2, RAPH1, CCNB3, CD3E, PIK3R5, TP73, PAK3, and AGAP2) were identified in PPI network. CIBERSORT analysis showed that activated natural killer cells were significantly higher in dilated aorta with BAV. Conclusions These identified key genes and pathways provide new insights into BAV aortopathy. Activated natural killer cells may participate in the dilation of ascending aorta with BAV.
ObjectiveTo screen differential expression of genes in hepatocellular carcinoma (HCC) by bioinformatics method, and analyze its clinical significance and its possible molecular mechanism in HCC.MethodsThe HCC gene expression profile GSE101728 was picked out to analyze the differential expression genes. The hub genes were identified by STRING and Cytoscape. GO and KEGG analysis were carried out by using DAVID and PPI network were constructed by STRING. The relationship among the hub genes were analyzed by using GEPIA.ResultsA total of 1 082 DEGs were captured (354 up-regulated genes and 728 down-regulated genes). Meantime, 10 hub genes ［cyclin dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin A2 (CCNA2), polo-like kinase 1 (PLK1), laser kinase B (AURKB), cyclin of cell division 20 (CDC20), centromere protein A (CENPA), mitotic arrest defective protein 2 (MAD2L1), cyclin B2 (CCNB2), and kinesin family 2C (KIF2C)］ were identified, and its expression and clinical significance were verified by GEPIA. GO and KEGG analysis showed 10 hub genes were mainly enriched in cell division and cell cycle. Expressions of AURKB, CCNB1, and MAD2L1 were obviously positively correlated (P<0.05).ConclusionThis study analyzes the hub genes in the development of HCC by bioinformatics methods and provides valuable information for further research on the mechanism of HCC.
Objective A series of bioinformatics methods were used to identify ferroptosis related biomarkers in lupus nephritis (LN). Methods We retrieved sequencing data of GSE112943 from the GEO (Gene Expression Omnibus) database and screened LN differentially expressed genes. We searched for ferroptosis-related gene (FRG) through FerrDb database, and screened LN-FRG. We conducted enrichment analysis on the LN-FRGs using David online bioinformatics database and screened the core LN-FRG using cytoHubba. We used external data sets to verify the core LN-FRGs, constructed competing endogenous RNA networks, and conducted molecular docking analysis. Results A total of 37 LN-FRGs were selected through screening. These genes are mainly enriched in inflammation, immune regulation and ferroptosis related signaling pathways. Through the cytoHubba and external dataset validation, the key core LN-FRG of ATF3 (activating transcription factor 3) was ultimately identified, and its expression was significantly increased in LN (P<0.05). Molecular docking analysis showed that ATF3 was closely bound to SLC7A11 and NRF2, and may participate in the occurrence and development of LN through the microRNA-27-ATF3 regulation axis. Conclusion The pivotal gene ATF3 may participate in the inflammation and immune injury of LN through ferroptosis.
Objective To analyze the relationship between the expression of carbonic anhydrase 3 (CA3) in breast cancer tissues, its prognostic potential and the number of immune cells by a variety of online databases. Methods GEPIA2.0 and TIMER databases were used to analyze the difference of CA3 mRNA expression in breast cancer tissues. Bc-GenExMinerv4.7 database was used to analyze the difference of CA3 mRNA expression in breast cancer subcategories. Kaplan-Meier plotter, Bc-GenExMinerv4.7 and PrognoScan databases were used to analyze the effect of CA3 mRNA expression levels on prognosis of patient. LinkedOmics database was used to analyze of the biological behavior involved in CA3 co-expressed genes. TIMER database was used to analyze the relationship between CA3 mRNA expression and immune cells infiltration in breast cancer tissues. Results The expression of CA3 mRNA in breast cancer tissues was lower than that in normal breast tissues (P<0.05), and the expression levels of CA3 mRNA were higher in ER negative (P<0.05), PR negative (P<0.05), HER2 negative (P<0.05) and no lymphatic metastasis (P<0.05). In addition, the expression level of CA3 in breast cancer patients with high Ki67 expression was lower (P<0.05) and closely related to SBR and NPI grade (P<0.05). Breast cancer patients with low expression of CA3 mRNA had lower overall survivall, recurrence free survival, and disease free survival ( P<0.05). Ten of the top 50 positively correlated co-expressed genes screened out had low risk ratio (P<0.05), and 11 of the top 50 negatively correlated co-expressed genes screened out had high risk ratio (P<0.05). The expression of CA3 mRNA was positively correlated with CD4+ T cells and CD8+ T cells in breast cancer tissues (rs=0.175, P<0.001; rs=0.137, P<0.001), and negatively correlated with T cell failure markers LAG3, TIM-3 and PVRL2 (rs=–0.100, P<0.01; rs=–0.143, P<0.001; rs=–0.082, P<0.05). Conclusions The low expression of CA3 mRNA in breast cancer tissues is correlated with the occurrence, development and prognosis of breast cancer. CA3 can be used as a potential independent prognostic marker for breast cancer and may be related to immune infiltration.
To screen new tuberculosis diagnostic antigens and vaccine candidates, we predicted the epitopes of Mycobacterium tuberculosis latent infection-associated protein Rv2004c by means of bioinformatics. The homology between Rv2004c protein and human protein sequences was analyzed with BLAST method. The second structures, hydrophilicity, antigenicity, flexibility and surface probability of the protein were analyzed to predict B cell epitopes and T cell epitopes by Protean software of DNAStar software package. The Th epitopes were predicted by RANKPEP and SYFPEITHI supermotif method, the CTL epitopes were predicted by means of combination analyses of SYFPEITHI supermotif method, BIMAS quantitative motif method and NetCTL prediction method. The peptide sequences with higher scores were chosen as the candidate epitopes. Blast analysis showed that Rv2004c protein had low homology with human protein. This protein had abundant secondary structures through analysis of DNAStar software, the peptide segments with high index of hydrophilicity, antigenicity, surface probability and flexibility were widely distributed and were consistent with segments having beta turn or irregular coil. Ten candidates of B cell epitopes were predicted. The Th epitopes of Rv2004c protein were located after the 200th amino acid. Of 37 Th cell epitopes predicted, there were more epitopes of HLA-DRB1*0401 and HLA-DRB1*0701 phenotypes, and the MHC restrictive types of some Th cell epitopes exist cross overlap. Of 10 CTL epitopes predicted, there were more number and higher score of HLA-A2 restricted epitopes. Therefore Mycobacterium tuberculosis Rv2004c protein is a protein antigen with T cell and B cell epitopes, and is expected to be a new target protein candidate for tuberculosis diagnosis and vaccine.
Objective To identify potential hub genes and key pathways in the early period of septic shock via bioinformatics analysis. MethodsThe gene expression profile GSE110487 dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes were identified by using DESeq2 package of R project. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were constructed to investigated pathways and biological processes using clusterProfiler package. Subsequently, protein-protein interaction (PPI) network was mapped using ggnetwork package and the molecular complex detection (MCODE) analysis was implemented to further investigate the interactions of differentially expressed genes using Cytoscape software. Results A total of 468 differentially expressed genes were identified in septic shock patients with different responses who accepted early supportive hemodynamic therapy, including 255 upregulated genes and 213 downregulated genes. The results of GO and the KEGG pathway enrichment analysis indicated that these up-regulated genes were highly associated with the immune-related biological processes, and the down-regulated genes are involved in biological processes related to organonitrogen compound, multicellular organismal process, ion transport. Finally, a total of 23 hub genes were identified based on PPI and the subcluster analysis through MCODE software plugin in Cytoscape, which included 19 upregulated hub genes, such as CD28, CD3D, CD8B, CD8A, CD160, CXCR6, CCR3, CCR8, CCR9, TLR3, EOMES, GZMB, PTGDR2, CXCL8, GZMA, FASLG, GPR18, PRF1, IDO1, and additional 4 downregulated hub genes, such as CNR1, GPER1, TMIGD3, GRM2. KEGG pathway enrichment analysis and GO functional annotation showed that differentially expressed genes were primarily associated with the items related to cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, hematopoietic cell lineage, T cell receptor signaling pathway, phospholipase D signaling pathway, cell adhesion molecules, viral protein interaction with cytokine and cytokine receptor, primary immunodeficiency, graft-versus-host disease, type 1 diabetes mellitus. Conclusions Some lymphocytes such as T cells and natural killer cells, cytokines and chemokines participate in the immune process, which plays an important role in the early treatment of septic shock, and CD160, CNR1, GPER1, and GRM2 may be considered as new biomarkers.
